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Author Amft, Oliver ♦ Junker, Holger ♦ Tröster, Gerhard
Source CiteSeerX
Content type Text
Publisher IEEE Computer Society
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Drinking Arm Gesture ♦ Behavioural Medicine ♦ Inertial Body-worn Sensor ♦ Arm Gesture ♦ Automatic Dietary Monitoring ♦ Inertial Sensor ♦ Continous Movement Data ♦ Isolated Discrimination ♦ Typical Meal Intake ♦ Two-stage Recognition System ♦ Experimental Result ♦ Normal Clothing
Description We propose a two-stage recognition system for detecting arm gestures related to typical meal intake. Information retrieved from such a system can be used for automatic dietary monitoring in the domain of behavioural medicine. We demonstrate that arm gestures can be clustered and detected using inertial sensors. Such sensors can be integrated unobtrusively into normal clothing. To validate our method, experimental results including 384 gestures from two subjects are presented. Using an isolated discrimination based on HMMs an accuracy of 95 % can be achieved. When spotting the gestures in continous movement data, an accuracy of of up to 87 % is reached. 1
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2005-01-01
Publisher Institution In Proceedings of the Ninth IEEE International Symposium on Wearable Computers